class SmilePredDataSet(Dataset):
    def __init__(self):
        super().__init__()
        self.input_list, self.size = get_pred_list(pred_smile_list)

    def __getitem__(self, index):
        input = self.input_list[index]
        input = paddle.to_tensor(input).astype('int64')
        return input

    def __len__(self):
        return self.size

    def get_vocabs(self, index):
        model_translate = ''
        for k in index:
            w = dict[k]
            if w == '<eos>':
                model_translate = model_translate + '<eos>'
                break
            if w != '<pad>' and w != '<eos>':
                model_translate = model_translate + w
        return model_translate